SGLang
Fast serving framework for large language models and vision-language models, with a structured generation language for complex LLM programs.
Overview
SGLang combines a high-performance inference backend with a frontend language for expressing complex LLM interactions - multi-step reasoning, structured output, tool calls - as a single program the runtime can optimize as a whole, rather than as a series of separate API calls. It targets both raw serving throughput and expressiveness for complex agent-style workloads.
SGLang is a fit for teams that need high-throughput LLM serving combined with structured, multi-step generation patterns, a performance-focused alternative to vLLM (also in this catalog) that teams commonly benchmark against each other.
- Categories
- AI & Machine Learning
- Languages
- Python
- License
- Apache-2.0
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